Statistical Thinking
Lesson 1 of 1
  1. 1
    Let’s imagine we are working for the city government of the fictional city of Melody Metropolis. The mayor of Melody Metropolis wants to know more about the musicians who currently live in the city…
  2. 2
    To start our summary for the mayor, let’s describe some of the categorical variables in the musician dataset — those variables that contain qualitative information on the city’s musicians. Fi…
  3. 3
    Now that we’ve learned about some of the categorical variables in our musician dataset, it’s time to explore some numeric variables — those with quantitative data. There are a lot of ways we …
  4. 4
    Let’s return to our visualization of the distribution of musician ages. ![Bar plot showing the distribution of ages. Ages range from about 15 to 70. The frequencies determine the heights of the ba…
  5. 5
    As we’re moving through the numeric variables in our musician dataset, we come across some interesting details when we inspect the income variable. ![Plot showing the distribution of the income va…
  6. 6
    Let’s find an alternative measure to the mean. We want to find a value that represents the typical musician income, but we don’t want to use the actual values in the computation because the data ar…
  7. 7
    For our income data, the difference between the mean ($34,795) and median ($32,978) was only about $2,000. You may be wondering: Is the difference ever larger? Let’s imagine some very famous celeb…
  8. 8
    One measure that we haven’t covered that is usually talked about alongside the mean and median is the mode. The mode is defined as the value with the highest frequency, but we can also think of the…
  9. 9
    Aggregating data is a way of exploring variable relationships. We specifically looked at relationships between a numeric variable and a categorical variable, but we should also examine relationship…
  10. 10
    Congratulations! We’ve finished our summary report for the mayor of Melody Metropolis, and you’ve just completed the lesson on statistical thinking! We covered a lot of information, including: * S…

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